High Capacity Reversible Data Hiding Based on the Compression of Pixel Differences

Abstract

In this paper, we proposed a novel reversible data hiding method in encrypted image (RDHEI), which is based on the compression of pixel differences. In the proposed method, at the content owner’ side the image is divided into non-overlapping blocks, and a block-level image encryption scheme is used to generate the encrypted image, which partially retains spatial correlation in the blocks. Due to the spatial correlation, in each block the pixels are highly likely to be similar. Therefore, the pixel differences in all blocks are concentrated in a small range and can be compressed. By the compression of pixel differences, the data hider can vacate the room to accommodate secret data in the encrypted image without losing information. At the receiver’s side, the receiver can obtain secret data or retrieve the original image using different keys with no error. The experimental results demonstrate that, compared with existing methods, the proposed method can achieve a higher capacity and visual quality.

High-Capacity Reversible Data Hiding in Encrypted Images Based on Prediction Error Compression and Block Selection

“…Since the accuracy of the predictor will affect the distribution of the prediction errors, a more accurate predictor can reduce the length of the encoded sequence and increase the embedding rate because of the characteristics of the Huffman coding technique. erefore, we first evaluate the proposed predictor with the pixel difference technique from [43]. In Table 2, the sums of the absolute prediction errors of different cases are listed; a lower value indicates that the predictor has higher prediction accuracy.…”

“…erefore, the generated prediction errors can be effectively compressed. Inspired by [43], we also use the Huffman coding technique to compress prediction errors. e detailed encoding and compression procedures are as follows:…”

“…For our proposed scheme, we adaptively choose the prediction direction for each image. We first compare the embedding rates among our scheme and eight related schemes [34][35][36][39][40][41][42][43] for eight test images. In Table 6, the embedding rates of [34,35] are relatively low, because the conventional reversible data hiding techniques of the spatial domain have been adopted.…”

“…Scheme [39] adaptively compresses bit planes, so the embedding rate provided by this scheme is higher than the above bit plane schemes. Scheme [43] turns to compress the pixel differences; however, the spare room is not fully utilized. Since our scheme compresses the prediction errors and improves the prediction direction and block selection, it has the highest embedding rates for all eight images.…”

“…e binary bit-level difference in each embeddable block is also considered and compressed in [42]. e pixel differences in [43] are simply compressed using the Huffman coding technique. Unfortunately, redundancy is underutilized in these small block size schemes.…”